The book conclusively solves problems associated with the control and estimation of nonlinear and chaotic dynamics in &#xFB01;nancial systems when these are described in the form of nonlinear ordinary di&#xFB00;erential equations. It then addresses problems associated with the control and estimation of &#xFB01;nancial systems governed by partial di&#xFB00;erential equations (e.g. the Black&#x2013;Scholes partial differential equation (PDE) and its variants). Lastly it an offers optimal solution to the problem of statistical validation of computational models and tools used to support &#xFB01;nancial engineers in decision making.

The application of state-space models in &#xFB01;nancial engineering means that the heuristics and empirical methods currently in use in decision-making procedures for &#xFB01;nance can be eliminated. It also allows methods of fault-free performance and optimality in the management of assets and capitals and methods assuring stability in the functioning of &#xFB01;nancial systems to be established.

Covering the following key areas of &#xFB01;nancial engineering: (i) control and stabilization of &#xFB01;nancial systems dynamics, (ii) state estimation and forecasting, and (iii) statistical validation of decision-making tools, the book can be used for teaching undergraduate or postgraduate courses in &#xFB01;nancial engineering. It is also a useful resource for the engineering and computer science community